Dynamic changes in nocturnal blood glucose levels are associated with sleep-related features in patients with obstructive sleep apnea

Implications of sleep disorders for periodontitis

PURPOSE

Periodontitis is a chronic inflammatory disease caused by multi-factors. Sleep is a natural physiologic process, and the sleep duration, quality, and patterns might be associated with periodontitis. Meanwhile, periodontitis might in turn induce systemic inflammation and thus impact sleep in different ways as well.

METHODS

To investigate the bidirectional relationship between sleep disorder and periodontitis, a literature search was conducted to reveal the interaction and possible mechanism between these two diseases.

RESULTS

The results show that sleep disorders can affect the progression of periodontitis via some pathomechanisms, and periodontitis also has a reverse impact on sleep.

CONCLUSION

Although the epidemiologic and clinical trials found the possible associations between sleep disorder and periodontitis, their relationship is still not that explicit. Further studies are warranted to shed light on them, to improve preventive health care.

Sleep Apnea and Cardiovascular Risk in Patients with Prediabetes and Type 2 Diabetes

Obstructive sleep apnea (OSA) is a common but largely undiagnosed clinical condition, which is turning into a serious public health issue. Of note is that its prevalence is gradually increasing in parallel with the obesity and type 2 diabetes mellitus (T2DM) epidemics. The aim of this article is to comprehensively review the literature in order to evaluate the cardiovascular (CV) risk among patients with OSA and prediabetes or T2DM. OSA seems to be an independent risk factor for the development as well as the progression of T2DM, whereas it is associated with T2DM-related macrovascular and microvascular complications. OSA may also act as a potential risk factor for the presentation and development of CV disease, such as hypertension, coronary artery disease, heart failure, pulmonary hypertension, atrial fibrillation and other cardiac arrythmias, as well as stroke. OSA and T2DM also share common pathophysiological mechanisms leading to atherosclerosis. Considering that the coexistence of OSA and T2DM is an independent and cumulative risk factor for CV mortality, more so than the two diseases separately, clinicians and healthcare professionals should be aware of and screen for OSA in patients with T2DM. Notably, targeted therapy for both conditions seems to substantially improve CV prognosis.

Obstructive sleep apnea, prediabetes, and progression of type 2 diabetes: A systematic review and meta-analysis

Aims/Introduction

Obstructive sleep apnea (OSA) is related to prediabetes and diabetes. Whether patients with OSA have a higher risk of prediabetes/diabetes remains unclear. We aimed to carry out a meta‐analysis of published studies to evaluate the relationships between OSA and prediabetes and diabetes, and the impact of the severity of OSA on diabetes.

Materials and Methods

The PubMed, EMBASE and Cochrane databases were searched from January 2011 to July 2021. The associations between OSA and impaired fasting glucose, impaired glucose tolerance, impaired glucose regulation and diabetes mellitus were analyzed. We estimated the pooled odds ratios using fixed or random effects models. We included 25 studies comprising a total of 154,948 patients with OSA and risk factors for prediabetes/diabetes (20 and 16, respectively) in the analysis.

Results

OSA was associated with a higher risk of impaired fasting glucose, impaired glucose tolerance, impaired glucose regulation and diabetes mellitus in the cohort studies and cross‐sectional studies. The pooled odds ratios were 2.34 (95% confidence interval [CI] 1.16–4.72), 1.58 (95% CI 1.15–2.15), 1.65 (95% CI 1.12–2.42), 2.15 (95% CI 1.68–2.75) and 3.62 (95% CI 2.75–4.75), respectively. Subgroup analyses were based on the proportions of men and women. The results showed that OSA was a risk factor, and there was no significant difference between the two groups. The risk of diabetes increased with the severity of OSA.

Conclusions

The risk of developing prediabetes and diabetes was higher in patients with OSA.

Postprandial glucose and HbA1c are associated with severity of obstructive sleep apnoea in non-diabetic obese subjects

INTRODUCTION

Obstructive sleep apnoea (OSA) is an underdiagnosed condition frequently associated with glycaemic control impairment in patients with type 2 diabetes.

AIM

To assess the relationship between glycometabolic parameters and OSA in obese non-diabetic subjects.

METHODS

Ninety consecutive subjects (mean age 44.9 ± 12 years, mean BMI 42.1 ± 9 kg/m²) underwent polysomnography and a 2-h oral glucose tolerance test (OGTT).

RESULTS

OSA was identified in 75% of subjects, with a higher prevalence of males compared to the group of subjects without OSA (62% vs 32%, p = 0.02). Patients with OSA had comparable BMI (42.8 kg/m² vs 39.4 kg/m²), a higher average HbA1c (5.8% vs 5.4%, p < 0.001), plasma glucose at 120 min during OGTT (2 h-PG; 123 mg/dl vs 97 mg/dl, p = 0.009) and diastolic blood pressure (81.1 mmHg vs 76.2 mmHg, p = 0.046) than obese subjects without OSA. HbA1c and 2 h-PG were found to be correlated with the apnoea-hypopnoea index (AHI; r = 0.35 and r = 0.42, respectively) and with percent of sleep time with oxyhaemoglobin saturation < 90% (ST90; r = 0.44 and r = 0.39, respectively). Further, in a linear regression model, ST90 and AHI were found to be the main determinants of 2 h-PG (β = 0.81, p < 0.01 and β = 0.75, p = 0.02, respectively) after controlling for age, sex, waist circumference, physical activity, and C-reactive protein. Similarly, ST90 and AHI persisted as independent determinants of HbA1c (β = 0.01, p = 0.01 and β = 0.01, p = 0.01, respectively).

CONCLUSION

Beyond the traditional clinical parameters, the presence of a normal-high value of 2 h-PG and HbA1c should raise suspicion of the presence of OSA in obese subjects.

Sleep quality and glycaemic variability in a real-life setting in adults with type 1 diabetes

AIMS/HYPOTHESIS

Suboptimal subjective sleep quality is very common in adults with type 1 diabetes. Reducing glycaemic variability is a key objective in this population. To date, no prior studies have examined the associations between objectively measured sleep quality and overnight glycaemic variability in adults with type 1 diabetes. We aimed to test the hypothesis that poor sleep quality would be associated with greater overnight glycaemic variability.

METHODS

Data were collected in the home setting from 20 adults (ten male and ten female participants) with type 1 diabetes who were current insulin pump users. Simultaneous assessments of objective sleep quality (Zmachine Insight+) and continuous glucose monitoring (CGM) were performed over multiple nights (up to 15 nights) in each participant. Due to the real-life nature of this study, the participants kept their usual CGM alerts for out-of-range glucose values. Sleep quality was categorised as 'good' or 'poor' using a composite of objective sleep features (i.e. sleep efficiency, wake after sleep onset and number of awakenings) based on the National Sleep Foundation's consensus criteria. Glycaemic variability was quantified using SD and CV of overnight glucose values based on overnight CGM profiles.

RESULTS

A total of 170 nights were analysed. Overall, 86 (51%) nights were categorised as good sleep quality, and 84 (49%) nights were categorised as poor sleep quality. Using linear mixed-effects models, poor sleep quality was significantly associated with greater glycaemic variability as quantified by SD (coefficient: 0.39 [95% CI 0.10, 0.67], p = 0.009) and CV (coefficient: 4.35 [95% CI 0.8, 7.9], p = 0.02) of overnight glucose values, after accounting for age, sex, BMI and overnight insulin dose. There was large inter- and intra-individual variability in sleep and glycaemic characteristics. Both pooled and individual-level data revealed that the nights with poor sleep quality had larger SDs and CVs, and, conversely, the nights with good sleep quality had smaller SDs and CVs. No associations were found between sleep quality and time spent in the target glucose range, or above or below the target glucose range, where CGM alarms are most likely to occur.

CONCLUSIONS/INTERPRETATION

Objectively measured sleep quality is associated with overnight glycaemic variability in adults with type 1 diabetes. These findings highlight an important role of sleep quality in overnight glycaemic control in type 1 diabetes. They also provide a strong incentive to both patients and healthcare providers for considering sleep quality in personalised type 1 diabetes glycaemic management plans. Future studies should investigate the mechanisms linking sleep quality to glycaemic variability.

Impact of obstructive sleep apnea complicated with type 2 diabetes on long-term cardiovascular risks and all-cause mortality in elderly patients

BACKGROUND

The prognostic significance of obstructive sleep apnea (OSA) in elderly patients with type 2 diabetes is unclear. The aim of this study was to determine the risk of cardiovascular disease (CVD) and mortality in elderly patients with OSA complicated with type 2 diabetes compared to patients with OSA without type 2 diabetes.

METHODS

From January 2015 to October 2017, 1113 eligible elderly patients with OSA, no history of cardiovascular, ≥60 years of age, and complete follow-up records were enrolled in this consecutive multicentre prospective cohort study. All patients had completed polysomnography (PSG) examinations. An apnoea-hypopnoea index of ≥5 events per hour recorded by polysomnography was defined as the diagnostic criterion for OSA. We collected baseline demographics, clinical characteristics, sleep parameters and follow-up outcomes. The primary aim of this study was to identify the risk of incident major adverse cardiovascular events (MACE). Secondary outcomes were all-cause mortality, components of MACE and a composite of all events. Kaplan-Meier survival analysis and Cox proportional hazards models were used to evaluate whether type 2 diabetes was associated with incident events.

RESULTS

A total of 266 (23.9%) patients had OSA complicated with type 2 diabetes. MACE occurred in 97 patients during the median 42-month follow-up. Kaplan-Meier survival curves indicated a significant relationship between type 2 diabetes and MACE (log-rank P = 0.003). Multivariable Cox regression analysis showed that type 2 diabetes increased the risk of MACE (HR = 1.64, 95% CI:1.08-2.47, P = 0.019), hospitalisation for unstable angina (HR = 2.11, 95% CI:1.23-3.64, P = 0.007) and a composite of all events in elderly patients with OSA (HR = 1.70, 95% CI:1.17-2.49, P = 0.007). However, there were no significant differences in the incidence of cardiovascular death, all-cause mortality, MI and hospitalisation for heart failure between patients with and without diabetes (P > 0.05). The subgroup analysis demonstrated that females (AHR = 2.46, 95% CI:1.17-5.19, P = 0.018), ≥ 70 years (AHR = 1.95, 95% CI:1.08-3.52, P = 0.027), overweight and obese (AHR = 2.04, 95% CI:1.29-3.33, P = 0.002) with mild OSA (AHR = 2.42, 95% CI: 1.03-5.71, P = 0.044) were at a higher risk for MACE by diabetes.

CONCLUSION

OSA and type 2 diabetes are interrelated and synergistic with MACE, hospitalisation for unstable angina and a composite of all events development. Overweight and obese females, ≥ 70 years with mild OSA combined with type 2 diabetes presented a significantly high MACE risk.